In the project CardioViz we explore a novel system for long-term Electrocardiogram (ECG) monitoring. In contrast to conventional ECG monitoring, the system additionally provides means to capture contextual information, such as activity, location and photos. We investigate how contextual information can be helpful when assessing long term ECG data and when relating anomalies to certain real-world situations. We assume that contextual information correlated over time with the ECG data allows for a better understanding. In the prototype we show the ECG signal together with photos and notes overlayed on a map. It seems that by these hints users can more easily remember where they were and hence what situation might be related to a specific period in the ECG. CardioViz consists of a mobile phone based client application and web based backend. The client application uses the sensors in the phone (e.g. camera) as well as further sensors (ECG, Accelerometer, GPS) connected via Bluetooth.